vllm-feature-tutoriallisted

# vLLM Feature Tutorial Generator Generate a comprehensive code walkthrough tutorial document for a given vLLM feature or module. ## Workflow ### Step 1: Identify the Feature Extract the feature/module name from the user's request. Examples: - "spec decode" / "speculative decoding" - "chunked prefill" - "automatic prefix caching" - "tensor parallelism" - "KV cache management" - "continuous batching" - "LoRA" - "multimodal" ### Step 2: Research the Feature Gather information from multiple sources. This is the most important step — thorough research determines document quality. **2a. vLLM Official Documentation** - Fetch relevant pages from `https://docs.vllm.ai/en/latest/` using WebFetch - Look for design docs, API references, usage guides **2b. vLLM Source Code** - Use `gh api` or WebFetch to browse the vLLM GitHub repo (`vllm-project/vllm`) - Identify core source files for the feature (use GitHub code search or browse directory structure) - Read key implementation files to understand: - Core classes and their responsibilities - Key interfaces and method signatures - Data flow and control flow - Important algorithms and data structures **2c. Related Resources** - Search for relevant blog posts, papers, or design documents - Check vLLM GitHub discussions/issues for design rationale ### Step 3: Generate the Tutorial Document Read [references/style-guide.md](references/style-guide.md) for the complete document structure and formatting conventions. Key require